Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Use of multiple GPUs on shared memory multiprocessors for ultrasound propagation simulations

dc.contributor.authorJaros, Jiri
dc.contributor.authorTreeby, Bradley
dc.contributor.authorRendell, Alistair
dc.coverage.spatialMelbourne Australia
dc.date.accessioned2015-12-10T23:33:21Z
dc.date.createdJanuary 30-February 3 2012
dc.date.issued2012
dc.date.updated2016-02-24T08:52:16Z
dc.description.abstractThis paper outlines our effort to migrate a compute intensive application of ultrasound propagation being developed in Matlab to a cluster computer where each node has seven GPUs. Our goal is to perform realistic simulations in hours and minutes instead of weeks and days. In order to reach this goal we investigate architecture characteristics of the target system focusing on the PCI-Express subsystem and new features proposed in CUDA version 4.0, especially simultaneous host to device, device to host and peer-to-peer transfers that the application is going to highly benefit from. We also present the results from a CPU based implementation and discuss future directions to exploit multiple GPUs.
dc.identifier.urihttp://hdl.handle.net/1885/69255
dc.publisherAustralian Computer Society Inc.
dc.relation.ispartofseriesAustralasian Symposium on Parallel and Distributed Computing (AusPDC 2012)
dc.rightsAuthor/s retain copyrighten_AU
dc.subjectKeywords: 7-GPU system; CUDA; Multi core; PCI Express; Ultrasound simulation; Acoustic fields; Bandwidth; Cluster computing; Fast Fourier transforms; Interfaces (computer); Peer to peer networks; Program processors; Ultrasonic propagation; Ultrasonic transmission; 7-GPU system; Bandwidth; CUDA; FFT; Matlab; Multi-core; PCI-Express; Ultrasound simulation
dc.titleUse of multiple GPUs on shared memory multiprocessors for ultrasound propagation simulations
dc.typeConference paper
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.lastpage52
local.bibliographicCitation.startpage43
local.contributor.affiliationJaros, Jiri, College of Engineering and Computer Science, ANU
local.contributor.affiliationTreeby, Bradley, College of Engineering and Computer Science, ANU
local.contributor.affiliationRendell, Alistair, College of Engineering and Computer Science, ANU
local.contributor.authoruidJaros, Jiri, u5053499
local.contributor.authoruidTreeby, Bradley, u4982447
local.contributor.authoruidRendell, Alistair, u9507815
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor020301 - Acoustics and Acoustical Devices; Waves
local.identifier.absfor080205 - Numerical Computation
local.identifier.absseo890201 - Application Software Packages (excl. Computer Games)
local.identifier.ariespublicationf5625xPUB1970
local.identifier.scopusID2-s2.0-84869098403
local.type.statusPublished Version

Downloads

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
01_Jaros_Use_of_multiple_GPUs_on_shared_2012.pdf
Size:
754.43 KB
Format:
Adobe Portable Document Format